Dino

About

We build high-quality, lane-based training datasets for fine-tuning LLM assistants and tool-using agents.

Our "Lane Suite" is a modular set of supervised datasets (Lane 1-37) where each lane targets a specific capability: instruction-following discipline, tone control, conversation quality, safety/refusal behavior, structured outputs (JSON/tables/specs), and agent behaviors like search integration and grounded answering with citations.

Every release is schema-strict and training-ready (JSONL chat format with system/user/assistant messages), packaged with reproducible manifests/hashes and QC reports. The goal is simple: make fine-tuning outcomes more predictable by training behaviors as separate, composable modules instead of one messy dataset mix.